Why Business Leaders and Investors See AI as Support, Not a Substitute
- Business leaders and investors are increasingly discussing the potential role of AI in boardroom decision-making and governance.
- Perspectives from private equity highlight both opportunity and caution as boards explore AI for preparation, analysis and oversight.
- The focus remains on how AI can support boards without replacing human judgment, with clarity around accountability and governance guardrails.
At the International Franchise Association’s Annual Convention (IFA2026) last week, a phrase caught my attention at a leadership session: “AI as an additional board member.”
It was not presented as a literal proposal, nor as a suggestion that artificial intelligence should replace directors or assume fiduciary responsibility. Instead, it pointed to a broader question boards are beginning to ask about how AI might support preparation, analysis and oversight at the governance level.
Having spent the last several years working with boards, private equity firms and leadership teams across growth-stage and scaled businesses, I realized that this was not really a technology discussion, it was about oversight and stewardship.
The discussion quickly moved past novelty and into something more practical: how AI might help boards think more clearly while preserving the role of human judgment and accountability, particularly when viewed through the lens of governance and fiduciary responsibility.
Boards exist to exercise judgment, accountability and fiduciary oversight. Those responsibilities remain human. Andrew Alexander, managing director at Levine Leichtman Capital Partners, offered a similar view. “I like the idea of an AI agent as a board ‘participant,’ but I’m not supportive (yet) of that role as a ‘voting board member.’”
That perspective reflects how many experienced leaders are interpreting the idea. “AI should not be a replacement for human judgment,” Alexander added. “Instead, its value lies in acting as a highly capable advisor — one that can rapidly synthesize information, surface patterns, test assumptions and provide alternative perspectives.”
AI as Decision Support
Boards today oversee increasingly complex organizations while balancing significant demands on time and attention. In that context, AI’s most compelling role is as a decision-support capability that helps boards process information more efficiently and ask better questions.
Early use reflects that practical approach. According to a poll by Corporate Board Member and Diligent Institute, 50% of board directors use generative AI for meeting preparation, 39% use it to summarize information and 26% use it for benchmarking. Only 13% report using AI for more advanced purposes such as predictive analysis or real-time risk monitoring.
That leaves room to grow. Boards can explore how AI might improve pre-read materials, summarize large volumes of operational and financial data, stress-test strategy and identify risks that may not be explicitly flagged in management presentations.
Another consideration boards are beginning to discuss is how reliance on AI changes behavior in the boardroom. As Jim Waskovich, managing partner at Princeton Equity Group, cautioned, “If AI is right 9 out of 10 times, over time a board could lose vigilance and be lulled into over-trusting an emerging technology. You never assume perfection with a human. You might with a machine.”
Importantly, most leaders do not envision AI as a digital director. Instead, as Waskovich described it, “I suspect what you’ll see is AI as a ‘special assistant to the board.’ A very well-prepared analyst who never gets tired and has no political agenda.” The analogy is telling: AI supports the process, but accountability remains firmly with the board.
As the conversation gains traction, experienced investors consistently return to the same cautions. Role clarity is essential. AI should inform discussion, not drive decisions. Boards must remain explicit about where accountability resides and avoid treating AI outputs as conclusions rather than inputs.
Data Security and Confidentiality
Data quality and scope also matter. AI systems are only as useful as the data they can access, and boards will need to understand what information is included, what is excluded and how that shapes the outputs. That naturally leads to questions about security, confidentiality and whether companies rely on third-party platforms or build internal capabilities.
Perhaps the more subtle risk is over-reliance. As AI tools become more refined and widely used, there is a danger that boards place undue confidence in outputs that appear objective or definitive. Judgment and oversight remain central to effective governance.
What stands out about the discussion around AI in the boardroom is that it prompts boards to re-examine how assumptions are challenged and how decisions are supported.
Adoption is likely to be uneven and shaped by factors such as industry, scale, and risk tolerance. What does appear to be changing is the level of attention boards are giving to how AI fits into boardroom discussions and governance processes more broadly.
Regardless of how the language around it evolves, the underlying focus remains consistent: how boards can use modern tools deliberately, transparently and with appropriate guardrails. In that sense, AI’s role in the boardroom is less about novelty and more about supporting sound judgment rather than replacing it.
